Daniel Sargent

· Professor of History and Public Policy

University of California, Berkeley · Public Policy

Active 1939–2026

h-index174

Citations151.6k

Papers1.1k32 last 5y

Funding$378.2M2 active

Academic metrics are sourced from OpenAlex and public funding records; values may differ from Google Scholar.

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About

Daniel Sargent is a faculty member at the Goldman School of Public Policy at the University of California, Berkeley. His work focuses on history and public policy, contributing to the academic community through his research and teaching. As a professor of history and public policy, he is involved in exploring the intersections of historical analysis and policy development, aiming to inform and improve public policy through a historical perspective.

Research topics

Horticulture
Biology
Genetics
Gastroenterology
Medicine
Internal medicine
Surgery
Oncology

Selected publications

The Economics of the Vietnam War
Cambridge University Press eBooks · 2024-10-31
book-chapter1st authorCorresponding
Publisher DOI
Supplementary Figure 1 from KRAS Codon 12 and 13 Mutations in Relation to Disease-Free Survival in BRAF–Wild-Type Stage III Colon Cancers from an Adjuvant Chemotherapy Trial (N0147 Alliance)
2023-03-31
preprintOpen access
PDF file - 108KB, Predictive value of specific KRAS mutations in patients with BRAF-wild type resected stage III colon cancer treated with adjuvant FOLFOX chemotherapy with vs without cetuximab. Unadjusted hazard ratios (HR) for disease-free survival by KRAS mutation strata are shown for patients who were randomized during the period when KRAS-mutated and -wild type tumors were eligible. HR < 1 indicates benefit from cetuximab. No estimates produced due to insufficient sample size in…
Publisher DOI
Supplementary Figure Legend from KRAS Codon 12 and 13 Mutations in Relation to Disease-Free Survival in BRAF–Wild-Type Stage III Colon Cancers from an Adjuvant Chemotherapy Trial (N0147 Alliance)
2023-03-31
preprintOpen access
PDF file - 69KB
Publisher OA PDF DOI
Supplementary Figure 1 from Comparison of Continuous versus Categorical Tumor Measurement–Based Metrics to Predict Overall Survival in Cancer Treatment Trials
2023-03-31
preprintOpen accessSenior author
PDF file - 12KB, Plots of observed versus expected 1-year survival probabilities for N0026 based on models for each metric and a model with no metric, adjusting for treatment arm and sum of baseline tumor measurements.
Publisher DOI
Supplementary Figure Legend from Comparison of Continuous versus Categorical Tumor Measurement–Based Metrics to Predict Overall Survival in Cancer Treatment Trials
2023-03-31
preprintOpen accessSenior author
PDF file - 45KB
Publisher DOI

Recent grants

Cancer and Leukemia Group B Statistical Center
NIH · $95.3M · 1982–2015
Cancer Risk Assessment, Early Detection, and Interception Research Program
NIH · $127.2M · 1997–2030
Statistics Core
NIH · $154.4M · 2014–2026

Frequent coauthors

Richard M. Goldberg
Applied Physical Sciences (United States)
1059 shared
Steven R. Alberts
Mayo Clinic
656 shared
Jacqueline Benedetti
Université de Caen Normandie
417 shared
Qian Shi
Mayo Clinic
417 shared
Marc Buyse
408 shared
Greg Yothers
University of Pittsburgh
402 shared
Frank A. Sinicrope
Mayo Clinic in Arizona
396 shared
Carmen J. Allegra
University of Florida Health
366 shared

Labs

GSPP Student GroupsPI

Education

PhD, Biostatistics
University of Minnesota System
1996

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